1/19/14

In the USA, the rate of unemployment in December 2013
is 6.7%. It is 0.6% lower than in October. According to our model, this
dramatic fall during the last two months was expected. Actually, two years ago
we predicted the level of unemployment to fall between 6.0% and 6.4% by the end
of 2013 or the beginning of 2014.

So, we have been reporting on the decline in the
rate of unemployment in the US since
the beginning of 2012. We predicted a dramatic period of unemployment falling
down to the level of 6.2% (=-0.4%) in the fourth quarter of 2013. This
prediction was made after we accurately forecasted (on March 1, 2012) the rate
of unemployment in the US to fall down to 7.8% by the end of 2012. Here we update
our model and present the evolution of the unemployment rate in the second
quarter of 2013. Overall, the measured rate has been following our prediction.
We foresee the rate to fall down to 6% [±0.4%] in the fourth quarter of 2013 or
in the first
quarter of 2014.

In 2006, we developed
three individual empirical relationships between the rate of unemployment, u(t), price inflation, p(t), and the change rate of labour
force, LF(t), in the United States.
We also revealed a general relationship balancing all three variables. Since
measurement (including definition) errors in all three variables are independent
it may so happen that they cancel each other (destructive interference) and the
general relationship might have better statistical properties than the
individual ones. For the USA, the best fit model for annual estimates was a
follows:

u(t) = p(t-2.5) + 2.5dLF(t-5)/dtLF(t-5) + 0.0585 (1)

where inflation (CPI) leads unemployment by 2.5
years (30 months) and the change in labor force leads by 5 years (60 months).
We have already posted
on the performance of this model several times.

For the model in this post, we use monthly
estimates of the headline CPI, u, and labor force, all reported by the US
Bureau of Labor Statistics. The time lags are the same as in (1) but
coefficients are different since we use month to month-a-year-ago rates of
growth. We have also allowed for changing inflation coefficient. The best fit
models for the period after 1978 are as follows:

There is a structural break in 2003 which is
needed to fit the predictions and observations in Figure 1. Due to strong fluctuations
in monthly estimates of labor force and CPI we smoothed the predicted curve
with MA(24).

The structural break in 2003 may be associated
with the change of sensitivity of the rate of unemployment to the change of
inflation and labor force. Alternatively, definitions of all three (or two)
variables were revised around 2003, which is the year when new population
controls were introduced by the BLS. The Census Bureau also reports major
revisions to the Current Population Survey, where the estimates of labor force
and unemployment are taken from. Therefore, the reason behind the change in
coefficients night be of artificial character - the change in measuring units.

Figure 1 depicts the predicted and observed in
the rate of unemployment since the beginning of the 1960s. Figure 2 depicts the
observed and predicted rate of unemployment since 2006, including a forecast for the next 12 months. The model
showed that the rate will fall to 6.0 % by December 2013. For 114 observations
since 2003, the modelling error is 0.4% with the precision of unemployment rate
measurement of 0.2% (Census Bureau estimates in Technical Paper 66).
Hence, one may expect 6.0% [±0.4%]. So far, our model was accurate in major changes, with all observed short-term deviations returning to the predicted curve.

Figure 1. Observed and predicted rate of
unemployment in the USA.

Figures 2. The predicted and observed rate of unemployment since 2006. We
expect this rate to fall down to 6.0% (and likely below) in the beginning 2014. The red
andblack curves have to intercept
somewhere in 2014.

1/5/14

Economists are not physicists. Most visible economists tend to manipulate data in a way to be more visible by obtaining politically biased results to please lay public. Income inequality is the hottest topic of 2013. Almost all economists focus on increasing income inequality as reported by the BEA. The top 1% snatch more and more money from poor working people. When taking a closer look, the BEA tells a different story, however. Figure 1 displays the cumulative increase in GDP, Gross Personal Income (GPI), and Compensation of employees (CE) since 1929. All curves are normalized to 1960, i.e. all cross 1 in 1960. The most remarkable feature is that the GPI has been growing much faster than GDP since 1977 (by the way, the year of dramatic changes in income statistics). Therefore, the share of personal income has been growing. This tendency is still on and one can expect further gains in personal income.

The share of labor money or compensation of employees in the GDP has not been changing much, however. The working population gets practically the same share of GDP since 1929. So to say, the labor part of production is rock solid. And the capital part of production has been melting out since 1977. It is not a surprize that the increment in personal income obtained by the top 1% is extracted from the capital part of GDP or Gross Domestic Income, which this 1% ... owns anyway. Figure 2 gives some more details on the period since 1960.

The distribution of income reported by the Bureau of Labor Statistics proves that the CE (labor share) does not indicate any change in income inequality.

Krugman and Co actually complain that the capital part of GDP involved in production is consumed now by the top 1% in a greater proportion. But this is a different story absolutely not related to income inequality.

Figure 1 . The net increase in GDP, Gross Personal Income (GPI), and Compensation of employees (CE) since 1929. All curves are normalized to their respective values in 1960.

Check these journals

DISCLAIMER

This is a personal site reflecting only my personal opinion. Statements on this site do not represent the views or policies of my employer, past or present, or any other organisation with which I may be affiliated